Feature Matching
Feature matching is a computer vision technique used to identify and correspond distinctive points (features) between two or more images. It involves detecting keypoints (like corners or blobs) in images, describing them with feature descriptors (e.g., SIFT, ORB), and then matching these descriptors to find similarities or correspondences. This process is fundamental for tasks such as image stitching, object recognition, and 3D reconstruction.
Developers should learn feature matching when working on applications that require image alignment, object tracking, or scene understanding, such as in augmented reality, robotics, or medical imaging. It is essential for building systems that can automatically identify and match visual patterns across different images, enabling robust and efficient computer vision pipelines.